Computer vision systems are based on information obtained from various measuring devices. Information can be measured using e.g. a laser device, a measuring head or via recognition from an image. The information obtained can be utilized e.g. in quality control systems, where, on the basis of this information, it is possible to determine e.g. the correctness of shape of an object, coloring errors or the number of knots in sawn timber.
The accuracy of the measurement results can be evaluated on the basis of various criteria. Measurements may involve various error components, so it is essential to discriminate bad measurement results from good ones. The accuracy of the components can be assessed by using accuracy factors. However, it is not possible to determine the inaccuracies of individual measurements by using accuracy factors; instead, these are used to describe the accuracy of a system at a general level.
In a three-dimensional computer vision system, illuminated points are typically produced on the surface of an object by using a laser. By measuring these points illuminated on the surface of the object with at least two cameras, the coordinates of the point in a three-dimensional coordinate system are obtained. However, several cameras are normally used to measure the coordinates of the point. The image coordinates measured by each camera for the same point have an effect on the three-dimensional coordinate obtained, so when several cameras are used, the accuracy of measurement of the three-dimensional coordinates is improved with a certain probability depending on the measurement parameters. On the other hand, the accuracy of three-dimensional measurement deteriorates substantially if an incorrect measurement significantly deviating from the correct value is included in the image coordinates detected by the cameras.
Methods based on a quality factor of measurement results have been used in measurements performed using theodolites. In these measurements, the consistency of a given coordinate with an observation made by another theodolite is calculated. However, these methods can not be directly applied to computer vision systems implemented using cameras because theodolite measurement involves no lens errors and the height coordinate is derived from the orientational position of the theodolite. In a camera system, all dimensions of the coordinates are measured by calculating from an image.